Residual Life Estimation of a Fabricated Humidity Sensor Using AI

From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS).